This paper studies data from the wholesale fruit and vegetables market in Marseille. The special feature of the data is that we have details of counteroffers to the prices that were proposed by the seller even when no transaction took place. Each offer, counteroffer and refusal conveys...

Carbon pricing decisions by governments are prone to time-inconsistency, which causes the private sector to underinvest in emission-reducing technologies. We show that incentives for decarbonization can be improved if complementing carbon pricing with carbon contracts for differences, where the...

In this paper we show that carbon pricing is subject to time-inconsistency and we investigate solutions to improve on the problem and restore the incentive for the private sector to invest in low-carbon innovation. We show that a superior price-investment equilibrium can be sustained in the...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...

For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...

Motivated by a nonparametric GARCH model we consider nonparametric additive regression and autoregression models in the special case that the additive components are linked parametrically. We show that the parameter can be estimated with parametric rate and give the normal limit. Our procedure...

We examine under which conditions a cap-and-trade mechanism can deliver a dynamically efficient abatement pathway and contribute to a robust investment framework. For this we develop a numerical dynamic partial-equilibrium model that includes differentiated objective functions of different...

We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator and an empirical likelihood based one for the mean of the response variable are defined. Both the estimators are proved to be asymptotically normal, with...